Marcel Huysegoms

Scientist, team „Big Data Analytics“
Academic degree: M.Sc. Technomathematik

Fields of Research

• Applying Deep Learning for identifying corresponding microstructures in high-resolution images

  The goal of this project is to automatically detect and match cells between consecutive histological images that have been bisected during the cutting of the brain. In particular, siamese networks are being utilized and examined for the purpose of solving this task. The challenge however stems from the fact that only a small fraction of cells actually does appear within two neighboring sections while the sections themselves contain non-linear deformations. Based on the extracted information, it‘s subsequently possible to reconstruct the images in a precise manner which results in a digital, high-resolution 3D-model of the brain.

  Figure: Zoomed-In visualization of a cell that appears in 2 neighboring histological images and therefore is bisected.
  

• Developing of scalable HPC-algorithms that fully utilize the resources available at the Jülich Supercomputing Centre (JSC). In this regard distributed computing and GPU-accelerators build the foundation for any parallelization.
• Stitching and registration of high-resolution histology images of the brain using linear and non-linear transformation models.

Methodologies

• Digital Image Processing
• Machine Learning
• High Performance Computing
• Processing of Big Data

Contact